Revisiting the Excess Volatility Puzzle Through the Lens of the Chiarella Model
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摘要
We extend and recalibrate a modified Chiarella heterogeneous-agent model to allow for arbitrary long-term value drifts, enabling calibration on individual monthly series across indices, bonds, commodities and FX; we find substantial excess volatility (noise-trader–driven price volatility ≈4× fundamental volatility for stock indices) and frequent bimodality of mispricing distributions, and we characterise parameter identifiability via a sloppiness (Fisher/Hessian) analysis that reveals a hierarchy of stiff vs sloppy parameter combinations [page::0][page::9][page::11][page::13][page::16].
